Litigation: a threat to obstetric practice?

Claims that the practice of obstetrics is in crisis appear regularly in the media, but evidence for the claims is scarce. This article examines a range of evidence from Australia and overseas and explores the relationship between obstetric practice and litigation. While anecdotal evidence abounds, there is no hard evidence to confirm that litigation is the threat to obstetric practice that many practitioners strongly believe it is. It is likely that such practitioners respond by practising defensive medicine but this is very difficult to measure.     

Learning the structure of a simple rent-seeking game

This paper considers a form of the Tullock imperfectly discriminating rent-seeking game in which the contestants are uncertain about the value of a bias parameter in the probability of winning function. Beliefs about this unknown parameter are not constrained to be static; we consider two methods by which the players' prior beliefs on this parameter can be updated. First, we allow for information to emerge by considering the case in which the game is played twice, with the outcome of the first game known before the second begins. The identity of the winner of the first contest represents information which emerges endogenously that can be used to revise beliefs on the unknown bias parameter. Second, information can be produced outside of the model by an external agency; this gives rise to exogenous learning. We consider the consequences for rent-seeking in each of these two cases.     

Pressure and the division of a public budget

This paper considers the division of a public budget among competing interests. The planner determines the optimal allocation by maximizing a weighted social welfare function. These weights reflect society's attitudes to different recipient groups, and are not constrained to be constant. By exerting “pressure”, the recipients can attempt to manipulate the weights and hence influence the division of the budget. The amount of resources used on pressure, and the effects on the preference weights are calculated. An important parameter in the model is the elasticity of pressure, for which an appropriate estimate is presented from the case of competition for a share of a health services budget in Norway.     

A Classification Tree Approach to the Development of Actuarial Violence Risk Assessment Tools

Since the 1970s, a wide body of research has suggested that the accuracy of clinical risk assessments of violence might be increased if clinicians used actuarial tools. Despite considerable progress in recent years in the development of such tools for violence risk assessment, they remain primarily research instruments, largely ignored in daily clinical practice. We argue that because most existing actuarial tools are based on a main effects regression approach, they do not adequately reflect the contingent nature of the clinical assessment processes. To enhance the use of actuarial violence risk assessment tools, we propose a classification tree rather than a main effects regression approach. In addition, we suggest that by employing two decision thresholds for identifying high- and low-risk cases--instead of the standard single threshold--the use of actuarial tools to make dichotomous risk classification decisions may be further enhanced. These claims are supported with empirical data from the MacArthur Violence Risk Assessment Study.     

Mental Disorder, Violence, and Gender

Recent studies have reported comparable rates of violence among men and women with mental disorder, raising important issues for clinical risk assessment. This study examines the relationship between gender and violence using data from the MacArthur Violence Risk Assessment Study. Patients in acute psychiatric wards were interviewed 5 times over the year following their discharge to the community. Results showed some differences between men and women in the violence committed immediately following discharge, with rates for men being higher. But the prevalence of violence over the 1 year was similar for female and male discharged patients. However, there were substantial gender differences in the situational context of the violence committed. Men were more likely to have been drinking or using street drugs, and less likely to have been adhering to prescribed psychotropic medication, prior to committing violence. The violence committed by men was more likely to result in serious injury than the violence committed by women, and men were more likely than women to be arrested after committing a violent act. Women were more likely to target family members and to be violent in the home.     

Stochastic models of the Social Security trust funds

Each year in March, the Board of Trustees of the Social Security trust funds reports on the current and projected financial condition of the Social Security programs. Those programs, which pay monthly benefits to retired workers and their families, to the survivors of deceased workers, and to disabled workers and their families, are financed through the Old-Age, Survivors, and Disability Insurance (OASDI) Trust Funds. In their 2003 report, the Trustees present, for the first time, results from a stochastic model of the combined OASDI trust funds. Stochastic modeling is an important new tool for Social Security policy analysis and offers the promise of valuable new insights into the financial status of the OASDI trust funds and the effects of policy changes. The results presented in this article demonstrate that several stochastic models deliver broadly consistent results even though they use very different approaches and assumptions. However, they also show that the variation in trust fund outcomes differs as the approach and assumptions are varied. Which approach and assumptions are best suited for Social Security policy analysis remains an open question. Further research is needed before the promise of stochastic modeling is fully realized. For example, neither parameter uncertainty nor variability in ultimate assumption values is recognized explicitly in the analyses. Despite this caveat, stochastic modeling results are already shedding new light on the range and distribution of trust fund outcomes that might occur in the future.